For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...

The application of neural networks to halftone image processing has catalysed transformative advances in both the generation and restoration of digital images. By leveraging deep learning ...

Artificial intelligence was built to process data, not to think like us. Yet a growing body of research is finding that the internal workings of advanced language and speech models are starting to ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

AI neural networks, inspired by the human brain are a foundational technology in the field of artificial intelligence. They are designed to recognize patterns and make decisions with a level of ...

Neuro-symbolic AI is a unique form of artificial intelligence that combines the strengths of neural and symbolic AI architectures. This powerful AI model can model cognition, learning, and reason, ...

How do electrical signals become "about" something? Through purely physical processes, neural networks transform activity ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important? When you purchase through links on our site, we may earn ...